Understanding rheological hysteresis in soft glassy materials
Rangarajan Radhakrishnan, Thibaut Divoux, S\'ebastien Manneville, and, Suzanne M. Fielding

TL;DR
This paper uses numerical simulations within fluidity and soft glassy rheology models to analyze rheological hysteresis in soft glassy materials, revealing different hysteresis behaviors linked to shear banding and fluid type.
Contribution
It introduces a numerical approach to understanding hysteresis in soft glassy materials, explaining different hysteresis behaviors through shear banding tendencies.
Findings
Hysteresis loop area decreases monotonically with sweep time in simple yield stress fluids.
Hysteresis loop area exhibits a bell-shaped dependence on sweep time in viscosity bifurcating fluids.
Simulations agree qualitatively with experimental data across four different soft glassy materials.
Abstract
Motivated by recent experimental studies of rheological hysteresis in soft glassy materials, we study numerically strain rate sweeps in simple yield stress fluids and viscosity bifurcating yield stress fluids. Our simulations of downward followed by upward strain rate sweeps, performed within fluidity models and the soft glassy rheology model, successfully capture the experimentally observed monotonic decrease of the area of the rheological hysteresis loop with sweep time in simple yield stress fluids, and the bell shaped dependence of hysteresis loop area on sweep time in viscosity bifurcating fluids. We provide arguments explaining these two different functional forms in terms of differing tendencies of simple and viscosity bifurcating fluids to form shear bands during the sweeps, and show that the banding behaviour captured by our simulations indeed agrees with that reported…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
